Synthesis of Distributed Array Based on Energy Valley Optimizer

In this study, an array antenna synthesis optimization method based on the energy valley optimizer (EVO) is proposed to address the problem of high sidelobe of distributed array. For the distributed array pattern of isomorphic subarray, the EVO algorithm is used to optimize the subarray positions. For the pattern of isomerism subarray, under the constraints of the certain subarrays spacing and the number of array elements in each subarray, the EVO algorithm is used to optimize the position and the amplitude of array elements. The peak sidelobe level of the array can be suppressed effectively in both cases. The simulation results of the EVO algorithm are compared with that of the particle swarm optimization and genetic algorithm. The results show that the EVO algorithm has faster convergence speed, higher accuracy and stronger stability. Thus the EVO algorithm is more suitable in solving the comprehensive optimization problem of the distributed array pattern. Based on the simulation results, the actual antenna is introduced for distributed array analysis, which verifies the feasibility of the method in this study.